LLM Mart Basic
@llm-mart · Joined Jun 2026
Express.js routes, middleware, error handling, request/response patterns
Fastify routes, JSON Schema validation, plugin system, TypeScript type providers
Hono routes, OpenAPI, Zod validation
NestJS backend framework - modules, controllers, services, DI, guards, pipes, interceptors, exception filters, middleware, DTOs with class-validator
GraphQL API server with Apollo Server — schema, resolvers, context, error handling, data sources, plugins
GraphQL server for Fastify with Mercurius — loaders, subscriptions, federation, JIT compilation
GraphQL Yoga v5 server, Envelop plugins, subscriptions, error masking
Webhook patterns — receiving, sending, signature verification, and retry logic
Pino logging, Sentry error tracking, Axiom - structured logging with correlation IDs, error boundaries, performance monitoring, alerting
Pino, Axiom, Sentry installation - one-time project setup for logging and error tracking with source maps upload
Query optimization, caching, indexing, connection pooling, async patterns
Job queues, background processing, and task scheduling with BullMQ v5
Elasticsearch patterns -- client setup, index management, search DSL, aggregations, vector search, bulk operations, deep pagination
Meilisearch search engine patterns -- client setup, indexing, search, filtering, facets, geo search, multi-tenancy, task management
OpenAPI 3.1 specification, schema design, code generation
Chroma vector database -- collection management, automatic embedding, metadata filtering, document storage, query patterns
Pinecone serverless vector database -- index management, vector operations, metadata filtering, namespaces, hybrid search, inference API
Qdrant vector database -- collection management, point operations, payload filtering, named vectors, quantization, recommendations, snapshots
Weaviate vector database patterns with weaviate-client v3 -- collection management, vectorizer modules, hybrid search, filtering, generative search (RAG), multi-tenancy, batch imports
Modern CLI development combining oclif's command framework with Ink's React-based terminal rendering
Fourteen posts of being wrong in production, compressed to checkboxes
Healthy nodes, a quiet network, 300 restarts in three days, and a latency budget measured in milliseconds
Discovery worked. Ping worked. Every TCP connection timed out, and later the tunnel only worked when someone had a terminal open.
Every VM came back. The cluster did not. Declarative systems converge on config, and the datapath isn't config.
A surprising share of AI-in-the-terminal failures aren't the AI. They're zsh, and a version of bash from 2006.
A Claude Code plugin turns standalone project configuration into a namespaced, installable extension that teams and communities can update as one unit.
None of the safety came from the model. It came from six boring habits.
Skills package instructions and references. Subagents run work in a separate context and return results. They solve different problems and can be composed deliberately.
Six hours in, one step left, everything green, and the incident that didn't happen
CLAUDE.md carries persistent project context. Skills load reusable procedures when relevant. Separating stable facts from task-specific workflows keeps both easier to maintain.
Twenty minutes recovering secrets that never existed, and the one sentence from a human that ended it
An API request routing a model's tool call through an approval gate to a remote MCP server
31 config keys, two audits, and why the first one was wrong in both directions
The official MCP Registry stores standardized server metadata rather than package code. Publishers verify a namespace, describe installation or remote access, and submit immutable versions.
Everyone looks at the Dockerfile. The file that actually leaked the key was the project file.
Remote MCP authorization uses established OAuth standards, but secure integration still requires issuer validation, least-privilege scopes, protected token handling, and server-side enforcement.
"Copy it over and switch the reference" is two steps, and the outage lives in the one nobody checks
stdio fits local processes and prototypes. Streamable HTTP fits hosted services and shared integrations. The right choice follows where the capability runs and who must reach it.
The most important rule wasn't about what I could change. It was about what I was allowed to display.
Tools perform operations, resources expose readable context, and prompts provide reusable templates. Choosing the correct primitive makes an MCP server easier to understand and govern.
/schema
Schema
Check frontmatter against the schema
/scope
Scope
Pull knowledge into a project
/secrets
Secrets
Scan for credentials
/sources
Sources
Show what a claim rests on
/split
Split
Split an overloaded page
/stale
Stale
Find concept pages nobody has touched
/tags
Tags
Audit the tag vocabulary
/timeline
Timeline
How my sources developed over time
/trace
Trace
Show which pages an answer used
/typed-links
Typed links
Add relation types where they matter
/weekly
Weekly
The weekly review
/build
Build
Implement an approved plan or issue in its own worktree, run the gate, open the pull request.
/close-out
Close out
Close a finished session: sweep for unfinished work, ask once, land, file the follow-ups, hand off, tell the sessions that depend on this one, then archive.
/handoff
Handoff
Write the repository handoff file for the next session, and record any durable learning.
/land
Land
Merge an approved pull request, clean up its worktree and branch, then check whether a release is due.
/plan
Plan
Turn a topic or issue into a plan the reviewer approves in the native plan pane.
/research
Research
Answer a research question with parallel read-only gatherers and one synthesized digest.
/review
Review
Review the branch's diff in two fresh contexts — scope against the spec, then quality — and report findings only.
/ia-refine-prompt
ia-refine-prompt
Transform a vague prompt into precise, structured AI instructions
/build
Build
Implement an approved plan or issue in its own worktree, run the gate, open the pull request.
VCP 部署在 AI 模型 API 与前端应用之间,是面向AGI OS开发和探索的工业级基建示范项目。通过统一指令协议、多层级持久化记忆、分布式插件引擎及多 Agent 协作框架,将原本“无状态、无记忆、无工具调用能力”的大语言模型,彻底改造成拥有永久自我意识、物理世界操作权及群体协作智能的完整智能体系统。
1 views 0 likesThe open source Unity Dev Agent
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1 views 0 likesMARVIS-Agent: all-purpose credit risk agent for model development, validation, data processing, feature engineering, and strategy workflows.
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7 views 0 likes小红书/抖音/快手/视频号/B站 自媒体账号体检+爆款拆解工具。扫同赛道找对标、拆爆款为什么爆、诊断为什么没人看,顺手出可粘贴仿写初稿。支持带货电商模式。支持codex, claude code, workbuddy
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3 views 0 likesA power user focused interface for LLM base models.
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3 views 0 likesThe open-source AI research workbench for scientific research and agent workflows. Local-first, model-agnostic desktop app with extensible skills, MCP tools and…
4 views 0 likes🤖 Taskade MCP · Official MCP server and OpenAPI to MCP codegen. Build AI agent tools from any OpenAPI API and connect to Claude, Cursor, and more.
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4 views 0 likesACRYL - Agent Context Relay Yielding Lifecycles. One persistent workspace, one canonical context, any coding agent.
3 views 0 likesOkou connects to the tools your team already uses and does the work — across marketing, sales, engineering, and operations, under your control.
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1 views 0 likesPersistent memory extension for pi with daily logs, scratchpad, and optional qmd‑powered semantic search.
1 views 0 likesHermes Agent CN desktop app, Windows-First, built with Tauri, Typescript and Rust. Isolated Hermes Agent core insides.
2 views 0 likes